mlsanityData to 7 Oct 2026

High efficiency compression for object detection

arXiv 1710.11151 ↗First posted 30 Oct 2017eess.IV cs.CVcited by 23

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Abstract (arXiv)

Image and video compression has traditionally been tailored to human vision. However, modern applications such as visual analytics and surveillance rely on computers seeing and analyzing the images before (or instead of) humans. For these applications, it is important to adjust compression to computer vision. In this paper we present a bit allocation and rate control strategy that is tailored to object detection. Using the initial convolutional layers of a state-of-the-art object detector, we create an importance map that can guide bit allocation to areas that are important for object detection. The proposed method enables bit rate savings of 7% or more compared to default HEVC, at the equivalent object detection rate.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Oct 2017.

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Citing papers per year: 2021: 2; 2022: 8; 2023: 4; 2024: 4; 2025: 5.

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  1. 2022Image Coding for Machines with Omnipotent Feature Learningcited by 31
  2. 2022A Coding Framework and Benchmark towards Low-Bitrate Video Understandingcited by 17
  3. 2024Image Coding for Machines with Edge Information Learning Using Segment Anythingcited by 17
  4. 2024SMC++: Masked Learning of Unsupervised Video Semantic Compressioncited by 11
  5. 2022Video Coding for Machines with Feature-Based Rate-Distortion Optimizationcited by 7
  6. 2022Perceptual Video Coding for Machines via Satisfied Machine Ratio Modelingcited by 7
  7. 2023Image Coding for Machines with Object Region Learningcited by 7
  8. 2022AccMPEG: Optimizing Video Encoding for Video Analyticscited by 6
  9. 2024Scalable Image Coding for Humans and Machines Using Feature Fusion Networkcited by 6
  10. 2023Accuracy Improvement of Object Detection in VVC Coded Video Using YOLO-v7 Featurescited by 4
  11. 2023Base Layer Efficiency in Scalable Human-Machine Codingcited by 4
  12. 2022Saliency-Driven Versatile Video Coding for Neural Object Detectioncited by 3
11 more
  1. 2024Delta-ICM: Entropy Modeling with Delta Function for Learned Image Compressioncited by 3
  2. 2025Explicit Residual-Based Scalable Image Coding for Humans and Machinescited by 3
  3. 2021SFU-HW-Tracks-v1: Object Tracking Dataset on Raw Video Sequencescited by 2
  4. 2022Recognition-Aware Learned Image Compressioncited by 2
  5. 2023Hyneter: Hybrid Network Transformer for Object Detectioncited by 2
  6. 2025Guided Diffusion for the Extension of Machine Vision to Human Visual Perceptioncited by 2
  7. 2021Revisit Visual Representation in Analytics Taxonomy: A Compression Perspectivecited by 1
  8. 2022Video Coding for Machines: Partial transmission of SIFT featurescited by 1
  9. 2025Image Coding for Machines via Feature-Preserving Rate-Distortion Optimizationcited by 1
  10. 2025CompressAI-Vision: Open-source software to evaluate compression methods for computer vision taskscited by 1
  11. 2025Training-Free Adaptive Quantization for Variable Rate Image Coding for Machinescited by 1